Jim Hester

Check if a given package name is available to use. It checks the
name's validity. Checks if it is used on 'GitHub', 'CRAN' and 'Bioconductor'. Checks
for unintended meanings by querying Urban Dictionary, 'Wiktionary' and Wikipedia.

Track and report code coverage for your package and (optionally)
upload the results to a coverage service like 'Codecov' <http://codecov.io> or
'Coveralls' <http://coveralls.io>. Code coverage is a measure of the amount of
code being exercised by a set of tests. It is an indirect measure of test
quality and completeness. This package is compatible with any testing
methodology or framework and tracks coverage of both R code and compiled
C/C++/FORTRAN code.

The two main functionalities of this package are creating mock
objects (functions) and selectively intercepting calls to a given
function that originate in some other function. It can be used
with any testing framework available for R. Mock objects can
be injected with either this package's own stub() function or a
similar with_mock() facility present in the 'testthat' package.

Provides a simple interface to lookup and print R function
definitions, including C and C++ compiled code from .Call, .C, .Internal and
.External calls. Also lookup of S3 and S4 generics, including a
simple dialog to print any or all of the loaded methods for the generic.

This is a package to transform large, multi-nested lists into a more
user-friendly format. The initial focus is on making
processing of return values from `jsonlite::fromJSON()` queries more seamless,
but ideally this package should be useful for deeply-nested lists from an array
of sources.

Provides a simple type annotation for R that is usable in scripts,
in the R console and in packages. It is intended as a convention to allow other
packages to use the type information to provide error checking,
automatic documentation or optimizations.

The goal of 'vroom' is to read and write data (like
'csv', 'tsv' and 'fwf') quickly. When reading it uses a quick initial
indexing step, then reads the values lazily , so only the data you
actually use needs to be read. The writer formats the data in
parallel and writes to disk asynchronously from formatting.

A set of functions to run code 'with' safely and temporarily
modified global state. Many of these functions were originally a part of the
'devtools' package, this provides a simple package with limited dependencies
to provide access to these functions.

A 'Teradata' backend for 'dplyr'. It makes it possible to operate
'Teradata' database <https://www.teradata.com/products-and-services/teradata-database/>
in the same way as manipulating data frames with 'dplyr'.

Package for parsing Affymetrix files (CDF, CEL, CHP, BPMAP, BAR). It provides methods for fast and memory efficient parsing of Affymetrix files using the Affymetrix' Fusion SDK. Both ASCII- and binary-based files are supported. Currently, there are methods for reading chip definition file (CDF) and a cell intensity file (CEL). These files can be read either in full or in part. For example, probe signals from a few probesets can be extracted very quickly from a set of CEL files into a convenient list structure.

Provides R bindings to the 'Sundown' Markdown rendering library
(<https://github.com/vmg/sundown>). Markdown is a plain-text formatting
syntax that can be converted to 'XHTML' or other formats. See
<http://en.wikipedia.org/wiki/Markdown> for more information about Markdown.

Missing values are ubiquitous in data and need to be explored and
handled in the initial stages of analysis. 'naniar' provides data structures
and functions that facilitate the plotting of missing values and examination
of imputations. This allows missing data dependencies to be explored with
minimal deviation from the common work patterns of 'ggplot2' and tidy data.

The goal of 'pak' is to make package installation faster and
more reliable. In particular, it performs all HTTP operations in parallel,
so metadata resolution and package downloads are fast. Metadata and package
files are cached on the local disk as well. 'pak' has a dependency solver,
so it finds version conflicts before performing the installation. This
version of 'pak' supports CRAN, 'Bioconductor' and 'GitHub' packages as well.

The SummarizedExperiment container contains one or more assays,
each represented by a matrix-like object of numeric or other mode.
The rows typically represent genomic ranges of interest and the columns
represent samples.

The goal of 'pkg' is to make package installation faster and
more reliable. In particular, it performs all HTTP operations in parallel,
so metadata resolution and package downloads are fast. Metadata and package
files are cached on the local disk as well. 'pkg' has a dependency solver,
so it finds version conflicts before performing the installation. This
version of 'pkg' supports CRAN, 'BioConductor' and 'GitHub' packages as well.

Analyze lines of R code using tidy principles. This allows you to
input lines of R code and output a data frame with one row per function
included. Additionally, it facilitates code classification via included lexicons.

Provides low-level access to 'GDAL' functionality for R packages. The aim is to minimize
the level of interpretation put on the 'GDAL' facilities, to enable direct use of it for a variety of purposes.
'GDAL' is the 'Geospatial Data Abstraction Library' a translator for raster and vector geospatial data formats
that presents a single raster abstract data model and single vector abstract data model to the calling application
for all supported formats <http://gdal.org/>. Other available packages 'rgdal' and 'sf' also provide access to
the 'GDAL' library, but neither can be used for these lower level tasks, and both do many other tasks.